code: def test_multivariate_normal_dist_shape():
      num_var = 2
      means = mx.nd.array((0, 1))
      covar = mx.nd.array(((1, 0), (0, 0.5)))
      data = mx.nd.array((0.5, 0.8))
      policy_dist = MultivariateNormalDist(num_var, means, covar)
      log_probs = policy_dist.log_prob(data)
      assert log_probs.ndim == 1
      assert log_probs.shape[0] == 1
  
imports: import mxnet
  import numpy
  import os
  import pytest
  from scipy import stats
  import sys
  from rl_coach.architectures.head_parameters import PPOHeadParameters
  from rl_coach.architectures.mxnet_components.heads.ppo_head import CategoricalDist, MultivariateNormalDist, DiscretePPOHead, ClippedPPOLossDiscrete, ClippedPPOLossContinuous, PPOHead
  from rl_coach.agents.clipped_ppo_agent import ClippedPPOAlgorithmParameters, ClippedPPOAgentParameters
  from rl_coach.spaces import SpacesDefinition, DiscreteActionSpace
label_desc: Use image node_id 1 for calling a global function with example usage: test_multivariate_normal_dist_shape() without return types